Reading List

Use this as a curated reference list. Prefer official documentation for implementation details.

Machine Learning

• scikit-learn User Guide.
• Hands-On Machine Learning.
• StatQuest explanations for statistics and ML intuition.
• Google Machine Learning Crash Course.

Deep Learning

• PyTorch Tutorials.
• TensorFlow/Keras Guides.
• Deep Learning by Goodfellow, Bengio, and Courville.
• fast.ai practical deep learning material.

Transformers and LLMs

• Attention Is All You Need.
• The Illustrated Transformer.
• Hugging Face Transformers documentation.
• Provider documentation for structured outputs and tool calling.

RAG

• Vector database documentation for the selected tool.
• Elasticsearch/OpenSearch documentation for keyword and hybrid search.
• LlamaIndex and LangChain documentation for pattern comparison.
• Research and engineering posts on chunking, retrieval evaluation, and reranking.

Agents

• Model/provider tool calling documentation.
• Model Context Protocol documentation.
• Research on ReAct and tool-use patterns.
• Security writing on agent authorization and prompt injection.

Cloud and DevOps

• Docker documentation.
• Kubernetes documentation.
• Terraform documentation.
• Cloud provider architecture frameworks.
• Observability documentation for logs, metrics, and traces.

Security

• OWASP Top 10.
• OWASP Top 10 for Large Language Model Applications.
• Cloud provider security best practices.
• Secrets management documentation.

Product and Architecture

• Designing Data-Intensive Applications.
• Fundamentals of Software Architecture.
• Product discovery and lean experimentation references.
• System design interview references for architecture practice.